def test_nn_5():
x, y = load_tictactoe_csv("tic-tac-toeWBlanks.csv")
nn = NeuralNetwork(x, y, 20, .01)
nn.train(100000)
print(nn.loss())
print(nn.accuracy_calculator())
assert nn.loss() < .01
def test_nn_3():
x, y = load_tictactoe_csv("tic-tac-toeWBlanksSmall.csv")
nn = NeuralNetwork(x, y, 10, .004)
nn.train(10000)
print("3 " + str(nn.loss()))
print(nn.accuracy_calculator())
assert nn.loss() < .1
def test_nn_4():
x, y = load_tictactoe_csv("tic-tac-toeWBlanksTraining.csv")
nn = NeuralNetwork(x, y, 11, .00066)
# 10, 0.0003, Epoch: 10000 -> 76%
# 10, 0.0005, Epoch: 10000 -> 89%
# 10, 0.0007, Epoch: 10000 -> 89.5%
# 11, 0.00066, Epoch: 10000 -> 92.3%
# 11, 0.00066, Epoch: 100,000 -> 96.9%
# 11, 0.00066, Epoch: 200,000 -> 95.
nn.train(100000)
print("4 " + str(nn.loss()))
print(nn.accuracy_calculator())
assert nn.loss() < .001
